Honglin Wen

Orcid: 0000-0001-8263-1399

According to our database1, Honglin Wen authored at least 18 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
A Contextual Bandit Approach for Value-Oriented Prediction Interval Forecasting.
IEEE Trans. Smart Grid, 2024

Efficient Unit Commitment Constraint Screening under Uncertainty.
CoRR, 2024

Improving Sequential Market Clearing via Value-oriented Renewable Energy Forecasting.
CoRR, 2024

Tackling Missing Values in Probabilistic Wind Power Forecasting: A Generative Approach.
CoRR, 2024

Fast Unit Commitment Constraint Screening with Learning-Based Cost Model.
Proceedings of the IEEE International Conference on Communications, 2024

2023
Optimal Adaptive Prediction Intervals for Electricity Load Forecasting in Distribution Systems via Reinforcement Learning.
IEEE Trans. Smart Grid, July, 2023

Deriving Loss Function for Value-oriented Renewable Energy Forecasting.
CoRR, 2023

Value-oriented Renewable Energy Forecasting for Coordinated Energy Dispatch Problems at Two Stages.
CoRR, 2023

Probabilistic Wind Power Forecasting with Missing Values via Adaptive Quantile Regression.
CoRR, 2023

Fast Constraint Screening for Multi-Interval Unit Commitment.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition.
ACM Trans. Multim. Comput. Commun. Appl., 2022

Enabling Fast Unit Commitment Constraint Screening via Learning Cost Model.
CoRR, 2022

Targeted Demand Response: Formulation, LMP Implications, and Fast Algorithms.
CoRR, 2022

Continuous and Distribution-free Probabilistic Wind Power Forecasting: A Conditional Normalizing Flow Approach.
CoRR, 2022

Wind energy forecasting with missing values within a fully conditional specification framework.
CoRR, 2022

2021
Probabilistic Load Forecasting via Neural Basis Expansion Model Based Prediction Intervals.
IEEE Trans. Smart Grid, 2021

2020
Unearthing Details of Time Series of Load: A Dual-scale Input Structured LSTM Approach.
Proceedings of the e-Energy '20: The Eleventh ACM International Conference on Future Energy Systems, 2020

2019
Probabilistic Wind Power Forecasting via Bayesian Deep Learning Based Prediction Intervals.
Proceedings of the 17th IEEE International Conference on Industrial Informatics, 2019


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